Improve object recognition using UWB SAR imaging with compressed sensing
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초록
In this paper, the compressed sensing basic pursuit denoise algorithm adopted to synthetic aperture radarimaging is investigated to improve the object recognition. From the incomplete data sets for image processing, thecompressed sensing algorithm had been integrated to recover the data before the conventional back- projectionalgorithm was involved to obtain the synthetic aperture radar images. This method can lead to the reduction ofmeasurement events while scanning the objects. An ultra-wideband radar scheme using a stripmap syntheticaperture radar algorithm was utilized to detect objects hidden behind the box. The Ultra-Wideband radar systemwith 3.1～4.8 GHz broadband and UWB antenna were implemented to transmit and receive signal data of twoconductive cylinders located inside the paper box. The results confirmed that the images can be reconstructed byusing a 30% randomly selected dataset without noticeable distortion compared to the images generated by full datausing the conventional back-projection algorithm.
Abstract
In this paper, the compressed sensing basic pursuit denoise algorithm adopted to synthetic aperture radarimaging is investigated to improve the object recognition. From the incomplete data sets for image processing, thecompressed sensing algorithm had been integrated to recover the data before the conventional back- projectionalgorithm was involved to obtain the synthetic aperture radar images. This method can lead to the reduction ofmeasurement events while scanning the objects. An ultra-wideband radar scheme using a stripmap syntheticaperture radar algorithm was utilized to detect objects hidden behind the box. The Ultra-Wideband radar systemwith 3.1～4.8 GHz broadband and UWB antenna were implemented to transmit and receive signal data of twoconductive cylinders located inside the paper box. The results confirmed that the images can be reconstructed byusing a 30% randomly selected dataset without noticeable distortion compared to the images generated by full datausing the conventional back-projection algorithm.
참고문헌 (16)
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